Evidence map›Paper›PMID 42793894›Full record

ArticleEntropy (Basel, Switzerland)2026

Coupling Coordination Degree Evaluation of Regional Water Resources, Social Economy and Ecological Environment Composite System Based on Logical Multiplication of Connection Numbers and Stochastic Simulations.

Ziyu Wang, Juliang Jin, Liangguang Zhou, Rongxing Zhou, Chengguo Wu, Yi Cui, Yawei Wang, Chao Huang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ziyu WangCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.ORCID 0009-0006-8052-4833
Juliang JinCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Liangguang ZhouSchool of Geographic Engineering and Spatial Information, Chuzhou University, Chuzhou 239000, China.ORCID 0000-0001-9209-5091
Rongxing ZhouSchool of Environment and Energy Engineering, Anhui Jianzhu University, Hefei 230601, China.
Chengguo WuCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Yi CuiCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Yawei WangCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Chao HuangCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, China.

Funding

Chuzhou University 2026qd09Department of Science and Technology of Anhui Province 2208085US03Department of Science and Technology of Anhui Province 2308085US06National Natural Science Foundation of China 52379006National Natural Science Foundation of China 52409001National Natural Science Foundation of China U2240223
6 · The paper itself

Abstract

Traditional coupling coordination degree (CCD) evaluation methods fail to simultaneously ensure the accuracy and reliability of evaluation results. To overcome this limitation, a novel evaluation method that integrates the logical multiplication of connection numbers with stochastic simulations (ECCD-LMS) is developed to assess the CCD of regional water resources, social economy, and ecological environment (WSE) composite systems. The method adopts three-element connection numbers to quantify the comprehensive evaluation level of each system. Overall partial connection numbers and triangular fuzzy numbers then define dynamic value intervals for the connection number components, and the Monte Carlo method is integrated to simulate stochastic variation in each component. The simulated values are substituted into the logical multiplication of connection numbers to generate evaluation results that include both mean CCD estimates and 95% uncertainty intervals. The empirical application of ECCD-LMS in China's Jing River Basin indicated that the coupling coordination level of the regional WSE composite system exhibited an overall increasing tendency with fluctuations from 2012 to 2023. These fluctuations were closely associated with variations in the comprehensive evaluation level of the water resources system. Spatially, the disparities in evaluation grades among subregions gradually narrowed during the study period. Compared with traditional CCD evaluation methods, ECCD-LMS effectively corrects systematic overestimation while maintaining objectivity and produces more dispersed CCD estimates that reflect differences among evaluation samples with greater clarity. Furthermore, by outputting mean CCD estimates and 95% uncertainty intervals, ECCD-LMS outperforms traditional methods that only provide static point estimates. It thus enables robust and credible evaluation of the coupling coordination level of WSE composite systems under multiple sources of uncertainty, suggesting potential applicability across diverse regional contexts.

Indexed as

evaluation of coupling coordination degreeJing River Basinlogical multiplication of connection numbersoverall partial connection numberstochastic simulation

Identifiers

PMID42793894
PMCPMC13605627

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